<p class="0abstract">Image denoising is a technique for removing unwanted signals called the noise, which coupling with the original signal when transmitting them; to remove the noise from the original signal, many denoising methods are used. In this paper, the Multiwavelet Transform (MWT) is used to denoise the corrupted image by Choosing the HH coefficient for processing based on two different filters Tri-State Median filter and Switching Median filter. With each filter, various rules are used, such as Normal Shrink, Sure Shrink, Visu Shrink, and Bivariate Shrink. The proposed algorithm is applied Salt&amp; pepper noise with different levels for grayscale test images. The quality of the denoised image is evaluated by usi

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

he paper presents the results of exposure of normal concrete to high temperatures (400 and 700°C). In addition to the exposure of steel reinforcement bar Ø 12 mm, where two types of steel reinforcement burning situations were performed. Directly exposed to high temperatures (400 and 700°C) and others were covered by concrete layer (15 mm). From the experimental results of fire exposure for 1 hour of 400 and 700°C and gradually cooled, it was found that the residual average percentage of compressive strength of concrete was 85.3 and 41.4%, while the residual average percentage of modulus of elasticity of concrete was 75 and 48%, respectively. The residual average percentage of yielding tensile stress (Ø 12 mm) after burning and cooling

Lignin has emerged as a promising asphalt binder modifier due to its sustainable and renewable nature, with the potential to improve flexible pavement performance. This study investigates the use of Soda Lignin Powder (SLP), derived from Pinus wood sawdust via alkaline treatment, as an asphalt modifier to enhance mixture durability. SLP was characterized using Fourier Transformation Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and Scanning Electron Microscopy with Energy Dispersive X-ray Analysis (SEM/EDX), revealing significant changes in its chemical structure post-extraction. These analyses showed the presence of phenolic units, including hydroxyphenyl propane, syringyl, and guaiacyl units. The morphology of SLP was identified

Worldwide, enormous amounts of waste cause major environmental issues, including scrap tires and plastic, and large waste, a consequence of the demolition of buildings, including crushed concrete, crushed clay bricks, and crushed thermo-stone. From that point, it’s possible to consider that the recycling processes for these materials and using them in the manufacturing field will reduce the adverse effects on the environment of these wastes and the consumption of natural resources. Sustainable concrete blocks can be considered as one of the products produced by using these materials as partial volume replacement of the coarse, fine aggregate, or cement content, considering their dry density, workability, absorption, compressive st